Tracking Moving Objects with Colored Speed Noise Using State Differencing

Resumen: To reduce errors while tracking a moving object trajectory with a colored speed noise, the Kalman and unbiased finite impulse response filtering algorithms are modified assuming the Gauss-Markov noise nature. The state differencing approach is employed, requires solving a nonsymmetric algebraic Riccati equation to avoid matrix augmentation. In this way, the system matrix is modified for colored process noise (CPN). The higher accuracy of the modified algorithms are validated using a simulated tracking model.

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J.A. Ortega-Contreras, Andrade Jose A. & Yuriy S. Shmaliy. Tracking Moving Objects with Colored Speed Noise Using State Differencing. Memorias del Congreso Nacional de Control Automático, pp. 1-6, 2020.

Palabras clave

Colored process noise, state differencing, Kalman filter, unbiased FIR filter

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